Monday 25th May 2015
Apple and Uber are developing their own self-driving cars.
Tesla intends to release a software update next month that will turn on “autopilot” mode, immediately allowing all Tesla Model S drivers to be driven between“San Francisco and Seattle without the driver doing anything”, in Elon Musk’s own words.
Tesla-driven humans won’t be able to legally let their cars do all the driving, but who are we kidding? There will be Teslas driving themselves, saving lives in the process, and governments will need to catch up to make that driving legal.
This process is already here in 2015. So when will the process end? When will self-driving cars conquer our roads?
According to Morgan Stanley, complete autonomous capability will be here by 2022, followed by massive market penetration by 2026 and the cars we know and love today then entirely extinct in another 20 years thereafter – Scott Santens
Wednesday 9th September 2015
Is a Cambrian Explosion Coming for Robotics?
Many of the base hardware technologies on which robots depend—particularly computing, data storage, and communications—have been improving at exponential growth rates. Two newly blossoming technologies—“Cloud Robotics” and “Deep Learning”—could leverage these base technologies in a virtuous cycle of explosive growth.
In Cloud Robotics—a term coined by James Kuffner (2010)—every robot learns from the experiences of all robots, which leads to rapid growth of robot competence, particularly as the number of robots grows.
Deep Learning algorithms are a method for robots to learn and generalize their associations based on very large (and often cloud-based) “training sets” that typically include millions of examples. Interestingly, Li (2014) noted that one of the robotic capabilities recently enabled by these combined technologies is vision—the same capability that may have played a leading role in the Cambrian Explosion.
How soon might a Cambrian Explosion of robotics occur? It is hard to tell.
The very fast improvement of Deep Learning has been surprising, even to experts in the field. The recent availability of large amounts of training data and computing resources on the cloud has made this possible; the algorithms being used have existed for some time and the learning process has actually become simpler as performance has improved.
The timing of tipping points is hard to predict, and exactly when an explosion in robotics capabilities will occur is not clear. Commercial investment in autonomy and robotics—including and especially in autonomous cars—has significantly accelerated, with high-profile firms like Amazon, Apple, Google, and Uber, as well as.
Human beings communicate externally with one another relatively slowly, at rates on the order of 10 bits per second. Robots, and computers in general, can communicate at rates over one gigabit per second—or roughly 100 million times faster. Based on this tremendous difference in external communication speeds, a combination of wireless and Internet communication can be exploited to share what is learned by every robot with all robots.
Human beings take decades to learn enough to add meaningfully to the compendium of common knowledge. However, robots not only stand on the shoulders of each other’s learning, but can start adding to the compendium of robot knowledge almost immediately after their creation.
The online repository of visually recorded objects and human activity is a tremendous resource that robots may soon exploit to improve their ability to understand and interact with the world, including interactions with human beings. Social media sites uploaded more than 1 trillion photos in 2013 and 2014 combined, and given the growth rate may upload another trillion in 2015.
The key problems in robot capability yet to be solved are those of generalizable knowledge representation and of cognition based on that representation. How can computer memories represent knowledge to be retrieved by memory-based methods so that similar but not identical situations will call up the appropriate memories and thoughts?
Significant cues are coming from the expanding understanding of the human brain, with the rate of understanding accelerating because of new brain imaging tools. Some machine learning algorithms, like the Deep Learning approached discussed earlier, are being applied in an attempt to discover generalizable representations automatically.
It is not clear how soon this problem will be solved. It may only be a few years until robots take off—or considerably longer. Robots are already making large strides in their abilities, but as the generalizable knowledge representation problem is addressed, the growth of robot capabilities will begin in earnest, and it will likely be explosive. The effects on economic output and human workers are certain to be profound. – Gill A. Pratt
Sunday 24th April 2014
George Hotz Scores $3.1m Investment for Self-Driving Car Startup Comma.ai
Comma hopes to sell road-worthy consumers car-automation ‘conversion kits’ for less than $1,000
Comma, has received $3.1m from well-known investment firm Andreessen Horowitz to make conversion kits that turn normal cars into semi-self-driving cars. Hotz plans to start selling these by the end of the year for Honda, Acura and potentially other brands.
For many consumers, automated vehicles still feel like science fiction and the province of giant research labs at Google, Uber and General Motors (GM). But there’s increasing evidence that many drivers’ first interaction with a self-driving vehicle will be one engineered by a small startup. Some of these companies are making automated public shuttles, or exploring ways to make existing cars autonomous in certain circumstances.
“We are going to win self-driving cars,” Hotz said in a recent interview. “The bar is low.”
That might seem like bold talk from a twentysomething who quit his day job at an artificial intelligence company last summer. But Hotz isn’t shy of attention. He recently challenged Tesla founder Elon Musk to a race to build the first vehicle that can navigate San Francisco’s tourist-packed Golden Gate Bridge on its own.
“I think we can maybe build better self-driving cars,” Hotz says. “He can build a better rocket.”
George Hotz’s Elon Musk dartboard (Photo credit: Chad McClymonds)
When asked what he would do with his new venture funds, Hotz said he would focus on hiring the best machine-learning programmers he could find. “Who I really want to hire is 20 more copies of me,” he says.
In December, Hotz made a name for himself when he showed Bloomberg Businessweek how he made an Acura drive itself down the highway. Hotz had hacked the car’s onboard computer. He then added a camera and a radar. Suddenly, the vehicle was cruising down Bay Area freeways as Hotz sat in the driver seat, his hands not on the steering wheel.
By the end of the year, Comma wants to sell consumers car-automation conversion kits for less than $1,000. Hotz is tight-lipped about what those will involve, but they will at least require some sort of alterations to a car’s onboard computer and hardware for the car to determine what’s going on around it.
Car automation has become increasingly democratized as much of the hardware behind the technology has fallen in price and the machine-learning techniques have been open-sourced. – Danny Yadron
Saturday 21st November 2015
Tesla Autopilot Prevents a 45mph Head-On Collision
Was travelling a little under 45 mph. There was some rain, but roads were pretty dry. I was watching stopped traffic to my right.
I did not touch the brake. Car did all the work. Sadly no audio, because I had an Uber passenger and Washington has strict privacy laws about recording conversations.
Saturday 18th June 2016
Elon Musk: We Are Less Than Two Years From Complete Car Autonomy
The Tesla CEO spoke at the Code Conference and predicted that we’re closer to self-driving cars than anybody thinks.
“I think we are less than two years away from complete autonomy, safer than humans, but regulations should take at least another year,” Musk said.
While many auto and tech companies–from Google to Uber and GM to Lyft and Apple to Ford–are researching and testing autonomous vehicles, Tesla seems on the verge of announcing that its Model 3 consumer sedan will have full self-driving capabilities.
Musk did not confirm that feature, but when asked multiple times on stage, he replied that there would be another Tesla event later in the year in which he would have more details.
The only thing he would say is that Tesla would do “the obvious thing”–seemingly a reference to a prior comment he made about autonomous driving being a must have feature for future vehicles. – Brian Soloman
Friday 30th September 2016
Singapore Blazes Self-Driving Taxi Trail
- Autonomous vehicle software start-up nuTonomy has announced that it is the first in the world to offer autonomous taxi rides. It beat Uber, which has started offering rides in autonomous cars in Pittsburgh
- Self-driving taxis can now be booked through an app by Grab, the biggest ride-hailing company in south-east Asia.
- NuTonomy and Grab won’t be the only providers of driverless, on-demand trips in Singapore. Last month, Delphi announced that it will provide a fleet of self-driving cars to the city-state.
Autonomous vehicle software start-up nuTonomy has made rides on its self-driving taxis available to the general public in Singapore for free, expanding a first-in-the world run that was initially invitation-only.
The Singapore trial was limited to a 2.5 square mile (6.5 square kilometre) business and residential district called One North.
NuTonomy CEO Karl Iagnemma said that the test area has since been doubled by the government. The approved route does not include any highways.
NuTonomy, a spin-off from the Massachusetts Institute of Technology (MIT), announced that the public can now book self-driving taxis through an app by Grab, the biggest ride-hailing company in south-east Asia. The two companies announced a year-long partnership.
To book a ride passengers will have to select the ‘robo-car’ option on Grab’s app. Passengers have to be older than 18 years old, book in advance and sign a liability waiver. Rides will be free for at least two months.
“We will be combining nuTonomy’s self-driving car software with Grab’s app, with their proven fleet routing technology and their mapping capabilities,” said Iagnemma.
The cars – modified Renault Zoe and Mitsubishi i-MiEV electrics – have a safety driver in front who is prepared to take the wheel and a researcher in the back, who watches the car’s computers.
If a pick-up or drop-off point is out of approved testing perimeters the driver will take over for the rest of the journey, Iagnemma said. “It’s an evolution to identify where are the easy parts, where are the trickier parts where we need to spend more time,” he said.
Iagnemma would not say how many rides nuTonomy provided in the trial period, but said thousands signed up for the invited trial within the first 48 hours. The company said there have been no problems and plans to make its Singapore taxi fleet fully self-driving by 2018. – The Gleaner
Friday 30th September 2016
Chris Dixon: In 2 years Everyone Will Use Driverless Cars on Highways
Within ten years, roads will be full of driverless cars.
Maybe within two, depending on where you’re driving.
That’s what Chris Dixon, a partner at prestigious Silicon Valley investment firm Andreessen Horowitz believes.
Dixon has written extensively about the future of autonomous vehicles and invested in a number of startups in the space, from self-flying delivery drones to, a company founded by a young man who built a self-driving car in his garage.
“All of the trends we’ve been observing over the last decade — from cloud computing to cheaper processing — have hit a tipping point,” Dixon says. “This is the core that’s getting people excited about AI, and specifically around autonomous vehicles and autonomous cars.”
It’s also cheaper than ever to build a smart car. Dixon says many driverless car companies use tiny chips made by a publicly-traded company, NVIDIA. NVIDIA’s chips only cost a couple hundred dollars.
“For $200, you could get what 10 years ago was a supercomputer on a little board and put it in your car, and it can run one of these sophisticated deep learning systems,” he says.
Additionally, a lot of the AI for autonomous vehicles is open-sourced, like Google’s product TensorFlow. This allows everyone in the space to create more accurate technology faster, because they can learn from each other’s data sets and build off the findings.
” I bet in two years, it will be the norm that on the highway, you’re not driving half the time or you’ll be using driver assistants heavily,” he says.
“It’s easier on highways and in suburbs,” says Dixon. “So you can imagine pushing a button on your Uber or Lyft app, and depending on the situation and location, an autonomous car comes or a person comes.”
He adds, “When will an Uber roll up without a person in it in New York City? That’s farther away. But I think that’s more like five years away, not 20.”
Dixon likens the promise of self-driving to Henry Ford’s Model T, which was like the iPhone of the time — a real technology game changer. At first, consumer cars seemed impossible — roads weren’t paved and no one knew how to drive cars. But the product was a hit, and everything changed to make way for them. – Alyson Shontell